Indexing multidimensional data is inherently complex leading to slow query processing. This behavior becomes more pronounced with the increase in database size and/or number of dimensions. In this paper, we address this issue by processing an index structure in parallel. First, we study different ways of partitioning an index structure. We then propose efficient algorithms for processing each query in parallel on the index structure. Using these strategies, we parallelized two multidimensional index structures -- R* and LIB and evaluated the performance gains for the Gazetteer and the Catalog data of the Alexandria Digital Library on the Meiko CS-2.
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index structure,multidimensional index structure,query processing,Catalog data,Indexing multidimensional data,Alexandria Digital Library,Meiko CS-2,database size,different way,efficient algorithm,Parallelizing Multidimensional Index Structures